Adoption of Account Based Marketing (ABM) Strategies Show No Signs of Slowing Down in 2019

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Casey joined Marketo, now part of Adobe, as vice president of product marketing in August 2018. Before joining Marketo, Casey held several product and marketing leadership positions at DoubleClick, Epsilon, Webtrends and Google, where he led marketing for the Advertiser and Publisher Platforms business. Casey began his career at Customer Insight Company, which was the first company to put a marketing database on a desktop computer.

Casey holds a Master of Business Administration focused in marketing and operations management from Regis University.

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Account-based marketing (ABM) is quickly becoming a preferred marketing strategy. In 2019, ABM will make an even bigger impact as AI-powered systems are more readily deployed as part of the strategy. What does that mean for you? More efficiency, easier implementation, better results, and a bigger bottom line, writes, Casey Carey, Sr. Director, Marketo Product Marketing, Adobe.

Over the past five years, marketing and sales teams have surpassed the fad stage of account-based marketing (ABM), arriving at a place where it is fast becoming a legitimate strategy for today’s B2B marketing. While it’s still relatively new, ABM is now a proven revenue driver as it capitalizes on today’s need for personalization in the chase for opportunities, conversions, and sales.

Alongside the increasing adoption of ABM, we’ve also seen a massive shift toward embracing AI. As companies continue to adopt AI, they’re also identifying new ways to apply this new technology to their respective industries. In fact, IDC forecasted that spending on cognitive and AI systems would reach $24 billion in 2018, and that number is expected to continue growing. As a result, it’s expected that marketing will see a surge in ABM strategies powered by AI in 2019, which will allow marketing teams to easily identify which accounts to focus on, validate target account lists with data, and turn lists into ABM campaigns, all at unprecedented scale and levels of efficiency.

Today’s ABM Challenges

To understand why integrating AI into ABM strategies is so powerful, we need to take a step back and look at the current state of ABM. One of the biggest challenges with ABM today is building the right target account lists as sales and marketing teams often have different opinions when it comes to identifying top targets. For example, sales teams often have quotas that they’re expected to meet by the end of the month or quarter, while marketing teams are expected to project trends and plan for campaigns months in advance. The difference between present and future thinking can result in drastically different priority targets between sales and marketing teams.

Alongside limited data, this discrepancy can often lead to lengthy processes to come up with a “top-tier” list, based little on fact and mostly on opinion. Additionally, because ABM account selection can be seen as complex and laborious, it’s often viewed as a “one and done” activity, resulting in lists that aren’t properly vetted and updated as relationships continue to evolve and new information becomes available.

The value of adopting an AI-powered ABM strategy

AI is a category of technology that encompasses using algorithms to model and predict outcomes like consumer behaviors based on large pools of data. As humans, we are able to do this every day — interpret data based on experiences we’ve had before and make a prediction based on those experiences. For example, because we know from past experiences that the highway is always backed up between 7-8 a.m., we know to take the back roads during that time, or perhaps, just leave a little earlier or later. This process seems automatic, but it demonstrates our ability to make a decision or predict a behavior based on previous experiences.

A similar process occurs when you adopt AI into your marketing team’s ABM strategy. By incorporating AI, your ABM campaigns can operate and analyze like we do every day.

AI can quickly examine millions of data points across an account, identifying the greatest opportunities for your products and services—a task that was previously manual and time-consuming for marketers. From there, sales and marketing teams can quickly develop a stratified account target list based on the data points analyzed and the desired business outcomes. This greatly diminishes the discrepancies between sales and marketing teams’ priority targets by aligning both departments to one goal, such as higher win rates in a certain customer category.

Additionally, because incorporating AI into ABM can result in a much quicker and more efficient target list development process, lists are much easier to update with just the click of a button. That means that priority lists can be updated alongside changing relationships, resulting in an opportunity for greater personalization and stronger customer experiences.

The future of AI-powered ABM

With AI as part of an ABM strategy, marketing teams will continue to see increased marketing and sales collaboration and efficiency, accelerated process and pipeline, and overall higher win rates.